We put the Google Pixel 8 Pro through our rigorous SBMARK Selfie test suite to measure its photo and video performance from an end-user perspective. This article analyzes the behavior of the device in a series of tests and several common use cases and aims to highlight the most important results of our tests with an excerpt of the acquired data.
Overview
Front camera main specifications:
- 10.5 MP sensor
- Lens with f/2.2 aperture
- 1.22 µm pixels
- Auto focus
- 4K video at 24/30/60 fps, (4K tested at 30 fps)
Pros
- Mostly accurate white balance in the photo
- Beautiful color rendering in indoor videos
- Generally accurate exposure in photos and videos
- Accurate focus on the face
- Generally good detail in daylight and indoors, for photos and videos
- Smooth video stabilization when panning
Against
- Occasional light color casts
- Slight noise in photos and videos
- Residual motion when holding the camera still while recording, slight focus instability in videos
- Artifacts due to depth estimation in bokeh mode
The Google Pixel 8 Pro delivered excellent performance in the SBMARK Selfie tests, nearing the top of our rankings and making it the best Android device to date. The Pixel 8 Pro uses similar front camera hardware as the Pixel 7 generation but adds autofocus. Overall, the camera showed significant improvements over previous models in both photo and video modes. In our tests, the Pixel 8 Pro performed particularly well in terms of color. Autofocus helped to significantly improve texture levels, especially in close-up shots, and therefore also led to a better texture/noise trade-off.
In video mode, the Pixel 8 Pro just edged out the class-leading Apple iPhone 15 Pro Max, thanks to accurate exposure, nice colors, and good detail. Video stabilization was smooth in panoramic shots, ensuring decent video performance overall.
Note that the Google Pixel 8 Pro was tested in SDR mode for Selfie because it provided better results than HDR mode, especially in terms of color.
Test summary
About SBMARK selfie tests: For scoring and analysis, SBMARK engineers capture and evaluate more than 1,500 test images in both controlled laboratory environments and natural outdoor, indoor, and low-light scenes, using default front camera settings. The photography protocol is designed to take user needs into account and is based on typical shooting scenarios, such as close-ups and group selfies. Evaluation is performed by visually examining images Cons a natural scene reference and performing objective measurements on laboratory-captured graph images under varying lighting conditions from 1 to 1,000+ lux and color temperatures from 2,300 K to 6,500 K. Learn more information about the SBMARK Selfie test protocol, click here. More details on how we rate smartphone cameras can be found here. The following section compiles key elements of SBMARK’s comprehensive testing and analysis. Full performance evaluations are available upon request. Please contact us to find out how to receive a full report.
Google Pixel 8 Pro selfie scores versus Ultra-Premium
This chart compares overall SBMARK Selfie scores for photos and videos between tested and reference devices. The average and maximum scores of the price range are also indicated. The average and maximum scores for each price segment are calculated based on the SBMARK device database.
Photo
143
Huawei Mate 50 Pro
Huawei Mate 50 Pro
Google Pixel 8 Pro Photo scores compared to Ultra-Premium
Photography tests analyze image quality attributes such as exposure, color, texture and noise under various lighting conditions. The focus range and presence of artifacts are also evaluated on all images captured under controlled laboratory conditions and in real-life images. All of these attributes have a significant impact on the final quality of images captured with the tested device and can help understand the camera’s key strengths and weaknesses.
In photo mode, the Google Pixel 8 Pro managed to maintain the nice, natural color rendition and wide dynamic range that we had already seen on the predecessor Pixel 7 Pro. It also added some significant improvements to the mix, particularly in terms of focus automatic focus and texture/noise compromise.
Note: For Google Pixel 8 Pro photos, we evaluated SDR files on an SDR display. The comparison photos of the Apple iPhone 15 Pro Max were evaluated using HDR files on an HDR display. Apple device HEIC files cannot be viewed on this page, so we use converted SDR files, which do not show the full potential of the iPhone.
Google Pixel 8 Pro – Accurate target exposure and pleasant color rendering
Exposure
90
Apple iPhone 15 Pro Max
Apple iPhone 15 Pro Max
Exposure is one of the key attributes for technically good images. The main attribute evaluated is the brightness of faces in various use cases and lighting conditions. Other factors evaluated are contrast and dynamic range, e.g. the ability to make details visible in both bright and dark areas of the image. Repeatability is also important because it demonstrates the camera’s ability to provide the same rendering when shooting consecutive images in a row.
Google Pixel 8 Pro – Bright face exposure, wide dynamic range in the background
Apple iPhone 15 Pro – Bright face exposure, wide dynamic range in the background
Huawei Mate 50 Pro – Bright face exposure, wide dynamic range in the background
The Pixel 8 Pro generally delivered accurate target exposure combined with a very wide dynamic range. However, the camera tended to err on the side of underexposed, to protect the highlighted areas of the frame.
Google Pixel 8 Pro – Underexposure of the face in backlit scenes
Google Pixel 7 Pro – Underexposure of the face in backlit scenes
Huawei Mate 50 Pro – Good facial exposure in backlit scenes
Color is one of the key attributes for technically good images. The image quality attributes analyzed are skin tone rendering, white balance, color shading and repeatability.
Color performance on the Pixel 8 Pro was consistent with that of its predecessor, predominantly producing a natural white balance. Additionally, Google’s RealTone outperformed many comparable features from the competition, offering exceptional color accuracy on skin tones.
Google Pixel 8 Pro – Pleasant skin tones, nice color on the sky and trees
Apple iPhone 15 Pro – Nice skin tones, nice color on the sky and trees
Huawei Mate 50 Pro – Less pleasant skin tone rendering
Focus
96
Apple iPhone 15 Pro Max
Apple iPhone 15 Pro Max
Autofocus tests evaluate the precision of focus on the subject’s face, the repeatability of accurate focus, and the depth of field. While a shallow depth of field can be nice for a single-subject selfie or close-up shot, it can be problematic in specific conditions like group selfies; both situations are tested. Focus accuracy is also evaluated in all real images taken, from 30cm to 150cm, and in low-light or outdoor conditions.
While the predecessor Pixel 7 Pro used a fixed focus lens, the Pixel 8 Pro now features an autofocus system in the front camera. In our tests, this helped significantly improve the level of subject detail, especially for close and long shooting distances.
Google Pixel 8 Pro: face and background in focus
Apple iPhone 15 Pro – Face and background in focus
Huawei Mate 50 Pro – slightly blurred on subject and background.
Structure
67
Asus ZenFone 7 Pro
Asus ZenFone 7 Pro
Texture tests analyze the level of detail and texture of subjects in images taken in the lab and in real-life scenarios. For natural shots, special attention is paid to the level of detail of facial features, such as the eyes. Objective measurements are performed on map images taken under various lighting conditions from 1 to 1000 lux and different types of dynamic range conditions. The papers used are the proprietary SBMARK (DMC) paper and the Dead Leaves paper.
Evolution of texture sharpness with illuminance level
This graph shows the evolution of texture sharpness with lux level for two holding conditions. Texture sharpness is measured on the Dead Leaves graph in the Close-up Dead Leaves setting.
On the latest Pixel Pro, the trade-off between noise and texture has been significantly improved, resulting in better overall performance in various lighting conditions and improved subject detail. Thanks to the new autofocus system, Pixel was able to capture good details from very short (30cm) to long (120cm and more) subject distances, providing a more consistent level of detail across all subject distances. subjects compared to previous models.
Noise
78
Huawei Mate 50 Pro
Huawei Mate 50 Pro
Noise tests analyze various noise attributes such as intensity, chromaticity, grain and texture on real images and on graph images taken in the laboratory. For natural images, particular attention is paid to noise on faces, but also to dark areas and high dynamic range conditions. Objective measurements are performed on graph images taken under various conditions from 1 to 1000 lux and different types of dynamic range conditions. The graph used is the SBMARK Dead Leaves graph and the standardized measurement such as visual noise derived from ISO 15739.
Evolution of visual noise with illuminance levels under handheld conditions
This graph shows the evolution of the visual noise metric with lux level in handheld conditions. The visual noise metric is the average of the visual noise measurement across all areas of the Dead Leaves graph in the Close-up Dead Leaves setting. SBMARK visual noise measurement is derived from the ISO15739 standard.
Compared to previous models, image noise was overall quite well under control (with behavior very similar to that of the Pixel 7 Pro and better performance than the iPhone15 Pro Max in this area), contributing to significant improvements in terms of texture/noise compromise.
Artifacts
90
Apple iPhone 15 Pro Max
Apple iPhone 15 Pro Max
Artifact evaluation looks at lens shading, chromatic aberrations, distortion measurements on the Dot and MTF graph, and sound measurements on the SFR graph in the lab. Particular attention is paid to ghosting, quantization, halos and tone changes on the face, among others. The more severe and frequent the artifact, the greater the point deduction from the score. The main artifacts observed and the corresponding point loss are listed below.
In terms of unwanted image artifacts, our testers observed only minor issues, and the Pixel 8 Pro performed very well overall in this category. That said, color quantization was evident on a few occasions, as was slight local texture loss in several test scenes (represented in the graph by the face rendering artifact score).
Major penalties for photography artifacts
Bokeh
70
Apple iPhone 15 Pro Max
Apple iPhone 15 Pro Max
Bokeh is tested in a dedicated mode, usually portrait or aperture mode, and analyzed by visually inspecting all images captured in the laboratory and in natural conditions. The goal is to reproduce a portrait photograph comparable to one taken with a DSLR and a wide aperture. The main image quality attributes that were paid attention to are depth estimation, artifacts, blur gradient, and the shape of the bokeh blur spotlights. The quality attributes of the portrait image (exposure, color, texture) are also taken into account.
The Pixel 8 Pro’s bokeh performance was very close to that of its predecessor the Pixel 7 Pro. Overall results were quite satisfactory, despite occasional inaccuracies in depth estimation, but achieving a DSLR-like natural blur gradient remained a challenge.
Google Pixel 8 Pro – Slight depth artifacts around the subject
Apple iPhone 15 Pro – Excellent subject isolation
Google Pixel 7 Pro – Slight depth artifacts around the subject
video
147
Apple iPhone 15 Pro Max
Apple iPhone 15 Pro Max
About SBMARK selfie video tests
SBMARK engineers capture and evaluate more than 2 hours of video in controlled laboratory environments and natural low-light scenes, indoors and outdoors, using default front camera settings. The evaluation consists of visual inspection of natural videos taken under various conditions and performing objective measurements on videos of graphs recorded in the laboratory under different conditions from 1 to 1000+ lux and color temperatures from 2,300 K to 6,500 K.
Google Pixel 8 Pro Video scores compared to Ultra-Premium
Video tests analyze the same image quality attributes as still images, such as exposure, color, texture, or noise, as well as temporal aspects such as speed, exposure uniformity and stability, white balance, and autofocus transitions.
In our front-facing camera video tests, the Google Pixel 8 Pro delivered a solid and consistent performance, falling just behind the best-in-class Apple iPhone 15 series.
Note that we tested video from the Google Pixel 8 Pro at both HDR and SDR settings and concluded that the SDR mode offered slightly better overall quality. It was then used for the comparisons below.
Exposure
84
Apple iPhone 15 Pro Max
Apple iPhone 15 Pro Max
Exposure tests evaluate facial brightness and dynamic range, e.g. the ability to make details visible in both bright and dark areas of the image. The stability and temporal adaptation of the exposure are also analyzed.
In our tests, the Pixel 8 Pro showed excellent exposure performance, with accurate target exposure, particularly in daylight and indoor lighting. However, the camera still struggles to get good target exposure in low light. The dynamic range was quite wide, showing slight improvements over the previous model, especially in low light conditions. Exposure transitions may be slower than competitors, but they were consistently accurate.
Google Pixel 8 Pro: Precise face exposure, wide dynamic range
Google Pixel 7 Pro: Precise face exposure, wide dynamic range
Apple iPhone 15 Pro – Precise face exposure, wide dynamic range, high contrast (on HDR displays)
Color
85
Apple iPhone 15 Pro Max
Apple iPhone 15 Pro Max
Image quality color analysis examines skin tone rendering, white balance, color shading, white balance stability and how it adapts when the light changes.
The camera’s color performance may sometimes struggle in daylight or low-light conditions. However, it was exceptional when recording indoors, particularly in terms of skin tones, which were remarkably accurate.
Google Pixel 8 Pro – Pleasant skin tones
Google Pixel 7 Pro – Pleasant skin tones
Apple iPhone 15 Pro – Pleasant skin tones
Focus
85
Huawei Mate 40 Pro
Huawei Mate 40 Pro
The new autofocus system was accurate most of the time but also exhibited some inconsistencies, particularly when tracking moving subjects. Overall, the addition of autofocus didn’t increase the focus score over its Pixel 7 Pro predecessor. However, it did help improve the texture score significantly, thanks to the new model’s ability to focus with accuracy over a wide range of subject distances.
Google Pixel 8 Pro: wide depth of field, fine details in the background
Google Pixel 7 Pro: wide depth of field, fine details in the background
Apple iPhone 15 Pro – Wide depth of field, good background details
Structure
85
Asus Zenfone 6
Asus Zenfone 6
Texture tests analyze the level of detail and texture of real videos and graphics videos recorded in the lab. Natural video footage is evaluated visually, with particular attention to the level of detail of facial features. Objective measurements are performed on chart images taken under various conditions from 1 to 1000 lux. The chart used is the Dead Leaves chart.
Like the photo mode, the video mode has improved significantly in terms of texture/noise trade-off, reaching a very good level. The autofocus system and its ability to achieve good focus over a wide range of subject distances play a substantial role in driving these improvements.
Google Pixel 8 Pro – Good details
Google Pixel 7 Pro – Good details
Apple iPhone 15 Pro – Good detail
Evolution of texture sharpness with illuminance level
This graph shows the evolution of texture sharpness with lux level for two holding conditions. Texture sharpness is measured on the Dead Leaves graph in the Close-up Dead Leaves setting.
Noise
68
Xiaomi Mi 11 Ultra
Xiaomi Mi 11 Ultra
Noise tests analyze various noise attributes such as intensity, chromaticity, grain, structure, temporal aspects on real video recordings and on videos of graphs taken in the laboratory. Natural videos are evaluated visually, with particular attention to noise on faces. Objective measurements are performed on graph videos recorded under various conditions from 1 to 1000 lux. The graph used is the SBMARK visual noise graph.
Evolution of spatial visual noise with illuminance level
This graph shows the evolution of spatial visual noise with lux level. Spatial visual noise is measured on the visual noise graph in the video noise setup. SBMARK visual noise measurement is derived from the ISO15739 standard.
Temporal evolution of visual noise with illuminance level
This graph shows the evolution of temporal visual noise with lux level. Temporal visual noise is measured on the visual noise graph in the video noise setup.
Stabilization
76
Apple iPhone 15 Pro Max
Apple iPhone 15 Pro Max
The stabilization rating checks the device’s ability to stabilize footage thanks to software or hardware technologies such as OIS, EIS or any other means. The evaluation examines overall residual motion on the face and background, smoothness, and gel artifacts, during walking and panning use cases under various lighting conditions. The video below is an excerpt of one of the scenes tested.
Stabilization performance remained efficient overall, with limited residual motion especially on handheld video. Stabilization was better than average when panning or walking while recording.
Google Pixel 8 Pro – Effective stabilization, slight residual movement on the subject, slight deformation of the background
Google Pixel 7 Pro – Effective stabilization, slight residual movement on the subject, slight deformation of the background
Apple iPhone 15 Pro – Effective stabilization, slight residual movement on the subject, no deformation of the background
In some specific cases, our testers observed some slight vibrations on videos shot with a tripod. These vibrations contributed to the score difference with the previous model. However, it is an issue that can be addressed with a firmware update.
Google Pixel 8 Pro – slight vibrations
Artifacts
87
Apple iPhone 12 mini
Apple iPhone 12 mini
Artifacts are evaluated with MTF and ringing measurements on the SFR graph in the lab, as well as frame rate measurements using the LED universal timer. Natural videos are visually evaluated by paying particular attention to artifacts such as quantization, hue shift, and face rendering artifacts, among others. The more severe and frequent the artifact, the greater the deduction of points from the score. The main artifacts and the corresponding point loss are listed below
Top penalties for video artifacts
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